Forecasting Spatially Dependent Origin and Destination Commodity Flows

29 Pages Posted: 13 Nov 2012

See all articles by James P. LeSage

James P. LeSage

Texas State University - McCoy College of Business Administration

Carlos Llano

Universidad Autónoma de Madrid

Multiple version iconThere are 2 versions of this paper

Date Written: November 12, 2012

Abstract

We explore origin-destination forecasting of commodity flows between 15 Spanish regions, using data covering the period from 1995 to 2004. The one-year-ahead forecasts are based on a recently introduced spatial autoregressive variant of the traditional gravity model. Gravity (or spatial interaction models) attempt to explain variation in N=n2 flows between n origin and destination regions that reflect a vector arising from an n by n flow matrix. The spatial autoregressive variant of the gravity model used here takes into account spatial dependence between flows from regions neighboring both the origin and destinations during estimation and forecasting. One-year-ahead forecast accuracy of non-spatial and spatial models are compared.

Keywords: gravity models, Bayesian spatial autoregressive regression model, spatial connectivity of origin-destination flows

JEL Classification: C11,C23,C31

Suggested Citation

LeSage, James P. and Llano, Carlos, Forecasting Spatially Dependent Origin and Destination Commodity Flows (November 12, 2012). Available at SSRN: https://ssrn.com/abstract=2174613 or http://dx.doi.org/10.2139/ssrn.2174613

James P. LeSage (Contact Author)

Texas State University - McCoy College of Business Administration ( email )

Finanace and Economics Department
601 University Drive
San Marcos, TX 78666
United States
512-245-0256 (Phone)
512-245-3089 (Fax)

HOME PAGE: http://www.spatial-econometrics.com

Carlos Llano

Universidad Autónoma de Madrid ( email )

Facultad de Ciencias Económicas y Empresariales
Departamento de Análisis Económico
Madrid, Madrid 28049
Spain
+34 914972910 (Phone)

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